docstr: Creates model and load weights from state
docstr_tok: ["Creates","model","and","load","weights","from","state"]
code: def _get_model_from_state(self, state):
      """Creates model and load weights from state"""
  
      # keep the same behavior as `set_state` in `load` do
      model = self.model_creator(self.config)
      model.set_weights(state["weights"])
  
      return model
  
imports: import itertools
  import logging
  import pickle
  import numpy
  import ray
  from zoo.common.utils import enable_multi_fs_load, enable_multi_fs_save
  from zoo.orca.data.ray_xshards import RayXShards
  from zoo.orca.learn.dl_cluster import RayDLCluster
  from zoo.orca.learn.tf2.tf_runner import TFRunner
  from zoo.orca.learn.ray_estimator import Estimator
  from zoo.orca.learn.utils import maybe_dataframe_to_xshards, dataframe_to_xshards, convert_predict_xshards_to_dataframe, update_predict_xshards, process_xshards_of_pandas_dataframe
  from zoo.orca.data.utils import process_spark_xshards
  from zoo.ray import RayContext
label_desc: Use image node_id 10 for calling the TensorFlow2Estimator obj's underlying member method code with example usage: obj._get_model_from_state(state) and returns: model